Assessment of an Exhaled Breath Test Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Lung Cancer

Abstract

Importance: Exhaled breath is an attractive option for cancer detection. A sensitive and reliable breath test has the potential to greatly facilitate diagnoses and therapeutic monitoring of lung cancer.

Objective: To investigate whether the breath test is able to detect lung cancer using the highly sensitive high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS).

Design, setting, and participants: This diagnostic study was conducted with a prospective-specimen collection, retrospective-blinded evaluation design. Exhaled breath samples were collected before surgery and detected by HPPI-TOFMS. The detection model was constructed by support vector machine (SVM) algorithm. Patients with pathologically confirmed lung cancer were recruited from Peking University People's Hospital, and healthy adults without pulmonary noncalcified nodules were recruited from Aerospace 731 Hospital. Data analysis was performed from August to October 2020.

Exposures: Breath testing and SVM algorithm.

Main outcomes and measures: The detection performance of the breath test was measured by sensitivity, specificity, accuracy, and area under the receiver-operating characteristic curve (AUC).

Results: Exhaled breath samples were from 139 patients with lung cancer and 289 healthy adults, and all breath samples were collected and tested. Of all participants, 228 (53.27%) were women and the mean (SD) age was 57.0 (11.4) years. After clinical outcomes were ascertained, all participants were randomly assigned into the discovery data set (381 participants) and the blinded validation data set (47 participants). The discovery data set was further broken into a training set (286 participants) and a test set (95 participants) to construct and test the detection model. The detection model reached a mean (SD) of 92.97% (4.64%) for sensitivity, 96.68% (2.21%) for specificity, and 95.51% (1.93%) for accuracy in the test set after 500 iterations. In the blinded validation data set (47 participants), the model revealed a sensitivity of 100%, a specificity of 92.86%, an accuracy of 95.74%, and an AUC of 0.9586.

Conclusions and relevance: This diagnostic study's results suggest that a breath test with HPPI-TOFMS is feasible and accurate for lung cancer detection, which may be useful for future lung cancer screenings.

Conflict of interest statement

Conflict of Interest Disclosures: Dr H Li reported receiving a patent for a handheld exhaled gas collector issued by Shenzhen Breatha Biological Technology Company, Ltd (202010621223). No other disclosures were reported.

Figures

Figure 1.. Flow Diagrams of Study Design and the Process of Support Vector Machine (SVM) Model Construction

The flow diagrams of study design (A) and the process of SVM model construction (B). C indicates parameter C, an important parameter in the SVM algorithm; EBUS-TBNA, endobronchial ultrasonography-guided transbronchial needle aspirate; LDCT, low-dose computed tomography.

Figure 2.. Exhaled Breath Sampling Equipment

Images show the design diagram (A) and sectional view (B) of the exhaled breath sampling equipment. The actual breath sampling equipment is connected with an air bag (C).

Figure 3.. Model Scores of Each Participant in Validation Data Set

The validation data set included 47 participants, with 28 individuals in the healthy control (HC) group and 19 patients with lung cancer (LC). Numbers on x-axis refer to participant identification numbers. BreLC indicates Breath Detector of Lung Cancer.